Seismic Foresight: A Novel Multi-Input 1D Convolutional Mixer Model for Earthquake Prediction Using Ionospheric Signals

Seismic Foresight: A Novel Multi-Input 1D Convolutional Mixer Model for Earthquake Prediction Using Ionospheric Signals

This study proposes a novel deep learning approach for predicting significant earthquakes (Mw <inline-formula> <tex-math notation="LaTeX">$\ge 5.0$ </tex-math></inline-formula>) in Turkey using ionospheric Total Electron Content (TEC) data and space weather indices....

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Bibliographic Details
Main Authors: Hakan Uyanik, Mehmet Kokum, Erman Senturk, Mohamed Freeshah, Salih T. A. Ozcelik, Muhammed Halil Akpinar, Serenay Celik, Abdulkadir Sengur
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
TEC signals
Earthquake precursor
space-weather indices
multi-input deep networks
ConvMixers
Online Access:https://ieeexplore.ieee.org/document/11053753/
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https://ieeexplore.ieee.org/document/11053753/

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